Multi-dimensional alignment between online instruction and course technology: A learner-centered perspective


This study examines the alignment between online instruction and course technology.

Instruction-technology fit is a formative construct comprising multiple dimensions.

Student satisfaction depends on online instruction, course technology and their fit.
Compared with face-to-face instruction, online instruction in distance and hybrid education relies on the extensive use of course technology. Course technology supports multiple aspects of online instruction including objective specification, material organization, engagement facilitation, and outcome assessment. This study looks into different dimensions underlying the alignment between online instruction and course technology, and investigates the direct and indirect effects of involved constructs on student satisfaction as the outcome variable. The empirical evidence from a survey supports most research hypotheses, and suggests that instruction-technology fit is a partial mediator for online instruction and a full mediator for course technology in terms of their relationships with student satisfaction. Whereas all alignment dimensions but assessment fit are significant, engagement fit calls for closer attention than objective fit and material fit. That is, course technology has great potentials as well as a big space for improvement to facilitate the student engagement aspect of online instruction. From a learner-centered perspective, the findings offer researchers and practitioners helpful insights on how to utilize all kinds of e-learning tools for student success.

Distance learning; Course technology; Online instruction; Instruction-technology fit; Student satisfaction

Student rules: Exploring patterns of students’ computer-efficacy and engagement with digital technologies in learning


A better understanding of student experiences in technologically integrated learning is needed.

Use of data mining techniques to uncover unique patterns among factors of technology integration.

Results show different patterns among students’ confidence and engagement in technology use.

More complex patterns were observed in students with negative engagement in technology use.

Results raise questions regarding how digital technologies are integrated in learning design.
Teachers’ beliefs about students’ engagement in and knowledge of digital technologies will affect technologically integrated learning designs. Over the past few decades, teachers have tended to feel that students were confident and engaged users of digital technologies, but there is a growing body of research challenging this assumption. Given this disparity, it is necessary to examine students’ confidence and engagement using digital technologies to understand how differences may affect experiences in technologically integrated learning. However, the complexity of teaching and learning can make it difficult to isolate and study multiple factors and their effects. This paper proposes the use of data mining techniques to examine unique patterns among key factors of students’ technology use and experiences related to learning, as a way to inform teachers’ practice and learning design. To do this, association rules mining and fuzzy representations are used to analyze a large student questionnaire dataset (N = 8817). Results reveal substantially different patterns among school engagement and computer-efficacy factors between students with positive and negative engagement with digital technologies. Findings suggest implications for learning design and how teachers may attend to different experiences in technologically integrated learning and future research in this area.